摘要
文章介绍一种基于推广分布表(GDT)和粗糙集的从不确定、不完整数据库中挖掘if-then规则的新方法.GDT是描述离散范畴的概念和实例的概率关系的表,通过使用GDT作为设定的搜索空间,将粗糙集与GDT相结合,可以处理噪声和未知实例.强度较大的if-then规则可以有效地按自底向上逐步增加的方式从大量的、复杂的数据库中获得.
There introduces a new approach for mining if-then rules in databases with uncertainty and incompleteness. The approach is based on the combination of Generalization Distribution Table （GDT） and the Rough Set methodology. A GDT is a table in which the probabilistic relationships between concepts and instances over discrete domains are represented. By using a GDT as a hypothesis search space and combining the GDT with the rough set methodology, noises and unseen instances can be handled, and if-then rules with strengths can be effectively acquired from large, complex databases in an incremental,bottom-up mode.
出处
《太原师范学院学报（自然科学版）》
2006年第1期37-40,共4页
Journal of Taiyuan Normal University:Natural Science Edition
基金
山西省教育厅高等学校科技开发项目(N0.20041335)
山西省忻州师范学院院级基金资助项目(NO.200303)
关键词
GDT
粗糙集
规则强度
冲突规则
GDT
rough set
strength of the rules
contradictory rules
